Method and its apparatus for inspecting particles or defects of a semiconductor device

ABSTRACT

Conventionally, a particle/defect inspection apparatus outputs a total number of detected particles/defects as the result of detection. For taking countermeasures to failures in manufacturing processes, the particles/defects detected by the inspection apparatus are analyzed. Since the inspection apparatus outputs a large number of detected particles/defects, an immense time is required for analyzing the detected particles/defects, resulting in a delay in taking countermeasures to a failure in the manufacturing processes. In the present invention, an apparatus for optically inspecting particles or defects relates a particle or defect size to a cause of failure in an inspection result. A data processing circuit points out a cause of failure from the statistics on the inspection result, and displays information on the inspection result. A failure analysis is conducted by setting a threshold for identifying a failure in each of regions on a semiconductor device or the like to statistically evaluate detected particles.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a divisional application of U.S. application Ser.No. 09/931,997, filed Aug. 17, 2001, now U.S. Pat. No. 6,797,975.

BACKGROUND OF THE INVENTION

The present invention relates to a method and apparatus for inspectingparticles or defects, and more particularly, to a method and apparatusfor inspecting particles or defects for use in inspecting particlesexisting on thin film substrates, semiconductor substrates, photomasksand so on, and pattern defects encountered on patterns on suchmaterials, and analyzing the cause of the defects in the manufacturingof semiconductor chips and liquid crystal products, wherein the methodand apparatus of the invention display an inspection result in such aform that enables the user to readily analyze the result and rapidlyidentify the cause of failure.

Conventionally, the technology for detecting defects on semiconductordevices and so on using an optical measuring means has been widelyknown. For example, “Semiconductor Wafer Inspection Apparatus” describedin JP-A-62-89336 discloses a technique for irradiating a semiconductorsubstrate with a laser to detect scattered light from particles, ifattached on the semiconductor substrate, and comparing the detectedscattered light with the result of an inspection, which has been madeimmediately before on the same type of semiconductor substrate, toinspect the particles or defects.

Also, “Method and Apparatus for Measuring Information on Particle orDefect Size” described in JP-A-5-273110 discloses a method of measuringsizes of particles or crystal defects, which involves irradiating anobject under inspection with a laser beam, receiving scattered lightfrom possible particles or crystal defects on the object underinspection, and processing the scattered light to generate an image ofthe object under inspection on which the sizes of particles and crystaldefects are measured.

Also, “Yield Monitoring and Analysis in Semiconductor Manufacturing” inprescripts of VLSI technology Seminar, pp. 4-42–4-47, in SEMICON Kansai,1997, discloses an approach for analyzing the yield from particlesdetected on a semiconductor wafer.

Conventionally, as an approach for managing product manufacturingprocesses in manufacturing lines for semiconductor substrates, thin filmsubstrates and so on, a management approach is employed for monitoringparticles and defects on substrates. Such a monitoring method involvesinspecting particles or pattern defects on substrates by use of anapparatus for inspecting particles or defects, monitoring a transitionof the number of particles or defects detected by the inspectionapparatus, and conducting a failure analysis on the particles or defectson substrates, from which a large number of particles or defects havebeen detected.

However, this prior art approach requires a total time for the failureanalysis equal to the product of the number of detectedparticles/defects and a time required for the failure analysis on oneparticle/defect. Particularly, the failure analysis requires aprohibitively long time when the particle/defect inspection apparatusdetects a large number of particles or defects, thereby giving rise to aproblem that the manufacturing of substrates is delayed.

SUMMARY OF THE INVENTION

The present invention has been made to solve the problem of the priorart as mentioned above, and provides a method and apparatus forinspecting particles or defects for use in inspection and failureanalysis on processes for manufacturing semiconductor wafers and thinfilm substrates, which are capable of performing an inspection inaccordance with sizes of particles and pattern defects or thecharacteristics of each region on an object under inspection to takeprompt countermeasures to a failure.

Specifically, the present invention provides a particle/defectinspection apparatus for measuring an object under inspection inaccordance with an optical approach to detect particles or defectsthereon. The inspection apparatus includes illuminating means forilluminating light to an object under inspection, light detecting meansfor detecting reflected light or scattered light from the object underinspection, detecting means for detecting particles or defects based ona signal detected by the light detecting means, dimension measuringmeans for processing the signal detected by the light detecting means tomeasure the size of each particle or defect, data processing means forprocessing an inspection result, and display means for displayinginformation on the inspection result, wherein the data processing meansrelates a particle or defect size to a cause of failure to point out thecause of failure from statistical processing on the inspection result,and the display means displays information on the inspection result.

The present invention also provides a particle/defect inspecting methodfor measuring an object under inspection in accordance with an opticalapproach to detect particles or defects thereon. The inspecting methodincludes a procedure for illuminating light to an object underinspection, a procedure for detecting reflected light or scattered lightfrom the object under inspection, a procedure for detecting particles ordefects based on a detected signal, a procedure for processing thedetected signal to measure the size of each particle or defect, a dataprocessing procedure for processing an inspection result, and aprocedure for displaying information on the inspection result. Theprocedures are executed in this order to relates a particle or defectsize to a cause of failure, wherein the data processing procedure pointsout a cause of failure from statistical processing on the inspectionresult to display information on the inspection result.

These and other objects, features and advantages of the invention willbe apparent from the following more particular description of preferredembodiments of the invention, as illustrated in the accompanyingdrawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram generally illustrating the configuration of anapparatus for inspecting particles or defects according to the presentinvention;

FIG. 2 is a block diagram of the apparatus for inspecting particles ordefects according to the present invention when it is operated as acomponent of a system;

FIG. 3A is a diagram showing image data when a particle exists;

FIG. 3B is a three-dimensional graph showing a distribution of signalstrength when particle data is measured;

FIGS. 4A and 4B are three-dimensional graphs for comparing distributionsof two types of signal strengths;

FIG. 4C is a graph for explaining how a maximum is calculated for thesignal strength;

FIGS. 5A to 5C are graphs showing the relationship between the particlesize and the number of detected particles depending on different causesof failure;

FIG. 6 is a graph showing the relationship between the number ofdetected particles and the particle size;

FIG. 7 is a histogram showing the relationship between the number ofdetected particles and the particle size;

FIGS. 8A and 8B are diagrams clearly illustrating particles of aparticular size on a wafer;

FIGS. 9A to 9C are graphs each showing in time series a transition ofthe number of detected particles having a particular size;

FIG. 10 is a front view of a screen which displays for the user a causeof failure which results in the generation of particles;

FIG. 11 is a plan view schematically illustrating regions on asemiconductor wafer;

FIGS. 12A and 12B are plan views each clearly showing particles of aparticular size on a wafer when particle data is managed separately foreach region;

FIG. 13 is a graph (No. 1) showing the relationship between the particlesize and the number of detected particles in each of regions;

FIG. 14 is a graph (No. 2) showing the relationship between the particlesize and the number of detected particles in each of regions;

FIG. 15 is a graph for explaining the relationship between a maximum ofsignal strength generated by the apparatus for inspecting particles ordefects according to the present invention and the particle size;

FIG. 16 is a block diagram illustrating the apparatus for inspectingparticles or defects according to the present invention which isoperated as a system together with a review apparatus;

FIG. 17A is a three-dimensional graph showing a distribution of asaturated signal strength;

FIG. 17B is a graph for explaining how a maximum is calculated for thesignal strength;

FIG. 17C is a plan view of a particle showing a major axis and a minoraxis of the particle;

FIG. 18A is a block diagram generally illustrating the configuration ofan inspection apparatus which has a function of distinguishing particlesfrom scratches;

FIG. 18B is a diagram for explaining a method of distinguishingparticles from scratches;

FIG. 19 is a block diagram illustrating a method of calculating theparticle size when using the method of distinguishing particles fromscratches;

FIG. 20 is a histogram showing the relationship between the number ofdetected particles and the particle size for a plurality of objectsunder inspection;

FIG. 21 is a histogram showing the relationship between the number ofdetected particles/scratches and the particle/scratch size separatelyfor particles and scratches;

FIG. 22 is a front view of a display showing a method of displayingdetected particles of particular sizes in the apparatus for inspectingparticles or defects according to the present invention;

FIG. 23 is a plan view of a wiring pattern for explaining therelationship between the wiring pattern and a particle size;

FIG. 24 is a graph showing the relationship between a detectionsensitivity and the influence of particles on a yield, when theapparatus for inspecting particles or defects according to the presentinvention is used;

FIG. 25 is a graph showing an example of calculating the influence onthe yield for each manufacturing step;

FIG. 26 is a graph showing the relationship between the particle sizeand the number of detected particles when standard particles aremeasured by the apparatus for inspecting particles or defects accordingto the present invention;

FIG. 27 is a graph showing the relationship between the particle sizeand the number of detected particles before calibrating the sensitivityfor the size of detectable particles in the apparatus for inspectingparticles or defects according to the present invention;

FIG. 28 is a graph showing the relationship between particle sizesmeasured by the inspection apparatus according to the present inventionand sizes measured by SEM when the sensitivity for the size ofdetectable particles is calibrated in the apparatus for inspectingparticles or defects according to the present invention;

FIG. 29 is a plan view of a wafer for explaining a method of calculatingthe influence on the yield from the presence or absence of particles;

FIGS. 30A and 30B are graphs showing correlations of particle sizesmeasured by the apparatus for inspecting particles or defects accordingto the present invention to particle sizes measured by SEM, where FIG.30A shows a correlation of particle sizes measured on a wafer having aone-layer pattern to particle sizes measured by SEM, and FIG. 30B is agraph showing a correlation of particle sizes measured on a wafer havinga multi-layer pattern to particle sizes measured by SEM;

FIG. 31 includes a graph showing a correlation of particle sizesmeasured by the apparatus for inspecting particles or defects accordingto the present invention to particle sizes measured by SEM, and SEMphotographs of detected particles;

FIG. 32 is a histogram showing the relationship between particle sizesand the number of the particles measured by the apparatus for inspectingparticles or defects according to the present invention;

FIG. 33A is a graph showing the relationship between particle sizesmeasured by the apparatus for inspecting particles or defects accordingto the present invention, and the yield;

FIGS. 33B and 33C are plan views of wafers each showing a distributionof detected particles on the wafer;

FIG. 34 is a graph showing an exemplary display of the accumulatednumber of particles by size, using the apparatus of inspecting particlesor defects according to the present invention; and

FIG. 35 is a graph showing the relationship between particle sizes andthe number of the particles measured by the apparatus for inspectingparticles or defects according to the present invention, together with adistribution of the detected particles.

DESCRIPTION OF THE EMBODIMENTS

In the following, each of embodiments according to the present inventionwill be described with reference to the accompanying drawings.

[Configuration and Operation of Apparatus for Inspecting Particles orDefects according to the Present Invention]

First, the configuration and operation of an apparatus for inspectingparticles or defects according to the present invention will bedescribed with reference to FIGS. 1 and 2.

FIG. 1 is a block diagram illustrating the configuration of theapparatus for inspecting particles or defects according to the presentinvention.

FIG. 2 is a block diagram of the apparatus for inspecting particles ordefects according to the present invention when it is operated as acomponent of a system.

While the following description on the embodiment will be made on anexample in which a semiconductor wafer is inspected for particlespossibly attached thereon, the present invention can be applied to anapparatus for inspecting pattern defects other than particles. Also, thepresent invention is not limited to semiconductor wafers but can beapplied to thin film substrates, photomasks, TFT, PDP and so on.

The apparatus for inspecting particles or defects according to thepresent invention comprises an illumination optical system 101; adetection optical system 103; a light detector unit 104; a signalprocessing circuit 105; a data display unit 106; a stage assembly 107;an auto-focus illumination unit 108; and an auto-focus light receiverunit 109.

For conducting an inspection, an object under inspection 102 is placedon the stage assembly 107 and irradiated by the illumination opticalsystem 101, and scattered light from the object under inspection 102 iscondensed by the detection optical system 103. Then, the light detectorunit 104 detects the scattered light from the object under inspection102. The scattered light detected by the light detector unit 104 isoptoelectrically transduced, and processed by the signal processingcircuit 105 to detect particles and measure their sizes.

The object under inspection 102 is moved in the horizontal direction bythe stage assembly 107, and also moved in the vertical direction by theauto-focus illumination unit 108 and auto-focus light receiver unit 109such that the object under inspection 102 is positioned at the focalpoint of the detection optical system 103. Thus, particles can bedetected and their sizes be measured over the entire area of the objectunder inspection 102. Then, the result of detection is displayed on thedata display unit 106.

Here, the illumination optical system 101 is configured to irradiate theobject under inspection 102 with light, for example, from a laser lightsource such as Ar laser, semiconductor laser, YAG laser and UV laser, ora white light source such as an Xe lamp and Hg lamp, using a beamexpander, a collimator lens, a cylindrical lens or the like. Theillumination optical system 101 is adjusted such that the light isirradiated at the focal point of the detection optical system 103.

Here, for selecting an appropriate light source, a light source having ashort wavelength is preferred as the illumination light source forimproving the sensitivity for detecting particles, so that a YAG laser,Ar laser and UV laser are suitable. Alternatively, for reducing the sizeand cost of the apparatus, a semiconductor laser is suitable. Furtheralternatively, a white light source is suitable as the illuminationlight source for reducing interference by an optically transparent thinfilm which may be formed on an object under inspection.

As to the shape of irradiating light, a circular illumination or a linerillumination may be used for irradiation. The illumination light may beor may not be collimated light. For increasing the amount of light on anobject under inspection per unit area, the power of the illuminationlight source may be increased, or the illumination light may beilluminated with high numerical aperture (NA).

Next, the detection optical system 103 has optical lenses configuredsuch that from the light emitted from the illumination optical system101, scattered light from the object under inspection 102 is condensedon the light detector unit 104. Also, the detection optical system 103also has the ability to optically process the scattered light, forexample, make modification, adjustment and so on to the opticalcharacteristics of the scattered light using a polarizer and a spatialfilter.

When a polarizer is used for optical processing, the polarizer ispreferably set up in a direction in which P-polarized light istransmitted when S-polarized light is irradiated. On the other hand, thepolarizer is preferably set up on a direction in which S-polarized lightis transmitted when P-polarized light is irradiated. When a spatialfilter is used, collimated light is suitably used as the illuminationlight for improving the performance of detecting particles.

The light detector unit 104 is used to receive the scattered lightcondensed by the detection optical system 103 for opto-electricallytransducing the scattered light, and is implemented, for example, by aTV camera, a CCD linear sensor, a TDI sensor, an anti-blooming TDIsensor, and a photomultiplier.

For selecting a device for the light detector unit 104, aphotomultiplier is suitable in use for detecting feeble light.Alternatively, a TV camera is suitable for rapidly capturing atwo-dimensional image. When the detection optical system 103 comprises afocusing system, a TV camera, a CCD linear sensor, a TDI sensor, or ananti-blooming TDI sensor is suitable. When the detection optical system103 comprises a light condenser system, a photomultiplier may be used.In addition, when the light detector unit 104 receives light over a widedynamic range, i.e., if the sensor is saturated by incident light, thesensor may be additionally provided with an anti-blooming function.

Next, the signal processing circuit 105 comprises a section fordetecting particles, and a section for measuring the size of a particle.For detecting particles, the signal processing circuit 105, for example,binarizes an input signal, determines a signal equal to or larger than abinarization threshold as a particle, and outputs the result ofdetermination. While the signal processing circuit 105 also measuresparticle sizes, details on associated processing will be describedlater. The stage assembly 107 in turn has functions of, for example,moving the object under inspection 102 in the horizontal and verticaldirections, and rotating the object under inspection 102. The auto-focusillumination unit 108 converges light emitted, for example, from a whitelight source such as an Hg lamp or a laser light source such as He-Neonto the object under inspection 102. Here, the wavelength of a lightsource used in the auto-focus illumination unit 108 is preferablydifferent from that of a light source used in the illumination opticalsystem 101.

Next, the auto-focus light receiver unit 109 is a section for receivinga portion of emitted from the auto-focus illumination unit 108, which isreflected from the object under inspection 102, and may comprise asensor capable of detecting the position of light, such as a positionsensor. Information acquired by the auto-focus light receiver unit 109is sent to the stage assembly 107 for controlling the stage. While inthe embodiment illustrated in FIG. 1, the illumination optical system101 illuminates the object under inspection 102 from one direction, theillumination optical system 101 may be configured to illuminate theobject under inspection 102 from two directions. Further, while theexample of FIG. 1 has one each of the detection optical system 103 anddetector unit 104 to detect the object under inspection 102 in onedirection, the inspection apparatus may comprise two or more sets ofthese components such that the object under inspection 102 is detectedin two or more directions.

Next, FIG. 2 illustrates a system which is configured using theapparatus for inspecting particles or defects according to the presentinvention. Specifically, the system comprises the particle inspectionapparatus 1301 of the present invention; a data server 1302; a reviewapparatus 1303; an electric testing apparatus 1304; an analyzer 1305;and a network 1306 for interconnecting the respective components. Inthis system, the review apparatus 1303 is, for example, a measuring SEM;the electric testing apparatus 1304 is a tester; and the analyzer 1305is an apparatus for analyzing components of particles such as EDX. Thedata server 1302 is a computer which can collect and accumulateinspection data from the particle inspection apparatus 1301; results ofreviews from the review apparatus 1303; results of tests from theelectric testing apparatus 1304; and results of analyses from theanalyzer 1305. The network 1306 is a communication network, for example,based on the Ethernet.

Next described will be the operation of the system using the apparatusfor inspecting particles or defects. After an inspection has been madein the particle inspection apparatus 1301, particles for whichappropriate countermeasures should be taken are selected by a method asdescribed above. Information on selected particles is added to theresult of inspection by the particle inspection apparatus 1301, forexample, serial numbers allocated to particles when they were detected,information on the positions of particles, information on the sizes ofparticles, and so on, and transmitted to the data server 1302 throughthe network 1306. For adding the information on the selected particles,for example, a flag may be added to the result of detection to indicatewhether or not appropriate countermeasures are required. Then, forinvestigating particles detected by the particle inspection apparatus1301 in greater detail, the object under testing is conveyed to thereview apparatus 1303. The object under testing may be manually conveyedor mechanically conveyed.

After the object under testing has been conveyed to the review apparatus1303, the review apparatus 1303 accesses the data server 1302 to receivethe result of detection from the data server 1302 through the network1306. Then, a review is started using the received result of detection.In this event, the particles which require countermeasures arepreferentially reviewed, using the information added by the particleinspection apparatus 1301, thereby making it possible to rapidly analyzeparticles which can cause a failure. Similarly, the analyzer 1305 canalso analyze preferentially the particles which require countermeasuresbased on the information added by the particle inspection apparatus1301, thereby making it possible to rapidly advance an analysis on thecause of a failure.

These review data and result of analysis may be accumulated in the dataserver 1302, such that they are matched with results of testing in theelectric testing apparatus 1304 to confirm whether or not a failure iseventually determined. If a failure is not eventually identified, thedata server 1302 transmits data for changing the criteria for selectingparticles which require countermeasures to the particle inspectionapparatus 1301, so that the particle inspection apparatus 1301 changesthe criteria for determining whether or not countermeasures arerequired, thereby making-it possible to more accurately select particleswhich require countermeasures and to readily take appropriatecountermeasures to a failure in the semiconductor manufacturing process.

While the foregoing description has been made for an example in whichdata is transmitted and received through a network, thetransmission/reception of data need not be performed through a network,but data may be delivered through a removable recording medium or sheetsof paper on which data are printed out.

Next described will be another manner of using the particle inspectionapparatus 1301 according to the present invention in combination of thereview apparatus 1303. FIG. 16 shows a portion of FIG. 2 extractedtherefrom. In FIG. 16, an inspection apparatus 1601 is, for example, theapparatus for inspecting particles or defects of the present invention,and a review apparatus 1602, for example, a measuring SEM, reviewsparticles or defects on an object under inspection. Also, a network 1603transmits/receives data between the inspection apparatus 1601 and thereview apparatus 1602, and is implemented, for example, by a systemconnected through the Ethernet. Next, the operation will be described.It should be noted that in the following description, particles aretaken as an example.

First, the inspection apparatus 1601 inspects particles on an objectunder inspection, and adds, for example, serial numbers allocated toparticles when they are detected, information on positions of particles,and information on sizes of particles to the result of inspection. Theresultant inspection data is transmitted to the review apparatus 1602through the network 1603. After the object under inspection is conveyedto the review apparatus 1602, the particles are reviewed in the reviewapparatus 1602. In this event, a scaling factor for reviewing in thereview apparatus may be adjusted in accordance with the information onthe particle sizes measured by the inspection apparatus 1602 to performan efficient reviewing operation. Specifically, when the particle sizeinformation acquired from the inspection apparatus 1601 shows a smallparticle, this particle is reviewed at a high scaling factor, so thatdetails on the small particle can be rapidly observed. On the otherhand, if the particle size information indicates a large particle, thisparticle is reviewed at a low scaling factor, so that the large particlecan be reviewed without extending off a review screen, thereby making itpossible to rapidly observe an entire image of the particle. Forexample, when the inspection data transmitted from the inspectionapparatus 1601 indicates a particle, the size of which is 0.1 μm, thisparticle is reviewed by adjusting the scaling factor such that thereview apparatus 1601 covers a field of view which spans 1 μm. On theother hand, when a particle has a size of 10 μm, the scaling factor isadjusted such that the review apparatus 1601 covers a field of viewwhich spans 100 μm. In this way, the review apparatus 1602 allows theuser to efficiently review small particles to large particles to rapidlyanalyze detected particles.

This embodiment has been described for an example in which particle sizeinformation is outputted from the inspection apparatus 1601, and thescaling factor is adjusted in accordance with the size information inthe review apparatus 1602. As an alternative method, information on thereview scaling factor and the field of view for reviewing in the reviewapparatus 1602 may be added to the inspection data.

Also, this embodiment has been described for an example in which aparticle is reviewed in the field of view which spans an area ten timeswider than the size of the particle by adjusting the review scalingfactor for the review apparatus 1602. However, the scaling factor may beany other value. Also, if the accuracy of particle position informationis known in the inspection apparatus 1601, a particle may be reviewed ata scaling factor based on the particle size information in considerationof the accuracy of the position information.

Further, while this embodiment has been described for an example inwhich a particle is reviewed by the review apparatus 1602, the foregoingapproach may be applied when a particle is reviewed by the apparatus forinspecting particles or defects of the present invention.

[Measurement of Size of Particle]

Next, description will be made on the processing for measuring the sizeof a particle using the method and apparatus for inspecting particles ordefects according to the present invention.

FIGS. 3A, 3B are a diagram showing image data when a particle exists,and a diagram showing a distribution of signal strength when particledata is measured.

FIGS. 4A to 4C are diagrams for comparing distributions of two types ofsignal strengths, and an explanatory diagram for showing how a maximumis calculated for the signal strength.

FIG. 3A shows an example of image processed by the signal processingcircuit 105 when a particle exists, where particle data 201 can be seenin a central portion of the image. The particle data 201 is outputtedfrom the light detector unit 104, and captured by the signal processingcircuit 105 as data having a contrast value. FIG. 3B shows FIG. 3A in athree-dimensional representation, where x- and y-axes are coordinateaxes for determining a position within the image, and z-axis representsthe signal strength. Signal strengths are plotted at correspondingpositions, and connected by lines. In FIG. 3B, a waveform 202 indicateswaveform data of the particle data 201. This waveform 202 can beapproximated to a Gaussian distribution from the nature of theillumination optical system 101 and the detection optical system 103,and the width and height of the Gaussian distribution vary depending onthe size of a particle on the object under inspection 102. Further, thewidth and height of the distribution also vary depending on theluminance of the laser illumination used in the illumination opticalsystem 101. Therefore, the shape of a distribution and the amount offeature may have been previously measured for a variety of standardparticles using the inspection apparatus of the present inventionconfigured as described above, such that the detected waveform 202 iscompared with the results of measurements made on the standard particlesto acquire information on the size of the detected particle.

A method of comparing the waveform 202 of the particle with thewaveforms of the standard particles may involve previously measuring thetotal sum (integral) of the signal strengths in the region occupied bythe particle data 201, i.e., data on the volume of the waveform 202, andcomparing the volume data of the particle data 201 with the volume dataof the standard particles. However, if the illumination optical system101 differs in luminance when the standard particles are measured andwhen particles on the object under inspection are measured, therespective volume data are divided by the luminances of the illuminationoptical system 101 for normalization, or the volume data of the particledata 201 or the standard particles is multiplied by the ratio ofluminances to correct the volume data.

As an alternative method of comparing waveforms, a maximum signalstrength value in the waveform 202 or the width of the waveform 202 maybe compared.

A method of calculating a maximum signal strength value will beexplained with reference to FIGS. 4A to 4C. FIGS. 4A, 4B show exemplarywaveforms of particle data, similar to the waveform 202.

Specifically, FIG. 4A shows an example in which a signal waveform ofparticle data acquired by the light detector unit 104 is in the shape ofpinnacle having a peak, indicating that the signal does not reach asaturation region of the light detector unit 104. FIG. 4B in turn showsan exemplary signal waveform of particle data which presents a plateaushape at the peak, indicating that the signal reaches the saturationregion of the light detector unit 104 and does not include dataexceeding the saturation region.

The maximum signal strength value is defined as the value which isdetermined as maximum as a result of comparison between signal strengthsat respective pixels of the waveform, when particle data draws a signalwaveform as shown in FIG. 4A, i.e., a signal strength at the peak point301. On the other hand, when particle data draws a signal waveform asshown in FIG. 4B, a calculation is performed as described below to finda maximum signal strength value.

First, in the saturation region 302, maximum lengths of the saturationregion are calculated in the x- and y-directions, respectively. FIG. 4Cshows a cross-section of FIG. 4B taken along the maximum length region.In FIG. 4C, the horizontal axis is a coordinate axis representing theposition in the maximum length region, while the vertical axis is acoordinate axis representing the signal strength. The signal strength303 indicates the saturation level of the light detector unit 104. Onthis cross-section, three or more unsaturated signals 304 are selected.Here, description is made on the assumption that three points areselected. As points to be selected, three points having the largestsignal strengths are selected from unsaturated signals on thecross-section. Assuming that the three points are at coordinates x1, x2,x3, and have signal strengths z1, z2, z3, respectively, equationsrepresenting Gaussian distributions are derived using unknown numbers k,σ, u:z 1=k/σ·exp(−(x 1−u)²/(2·σ²))z 2 =k/σ·exp(−(x 2−u)²/(2·σ²))z 3=k/σ·exp(−(x 3−u)²/(2·σ²))The unknown values k, σ, u can be found by solving the simultaneousequations. Then, the maximum signal strength value in FIG. 3B can becalculated using the resulting values of k, σ as follows:k/σ

It should be noted that although the example shown herein uses theunknown value u for calculating the maximum signal strength value, theunknown value u need not be used. In this case, two points are selectedfrom the unsaturated signals 304. Selected signal points are thosehaving the largest signal strengths from unsaturated signals on thecross-section. Assuming that the two points are at coordinates x1, x2,and have signal strengths z1, z2, respectively, equations representingGaussian distributions are derived using unknown numbers k, σ:z 1 =k/σ·exp(−(x 1)²/(2·σ²))z 2 =k/σ·exp(−(x 2)²/(2·σ²))

Since the unknown values k, σ can be found by solving the simultaneousequations, the maximum signal strength value in FIG. 3B can becalculated using the values of k, σ as follows:k/σ

A particle size can be measured by comparing the maximum signal strengthvalue derived from the foregoing calculation for a detected particlewith those for the standard particles.

Next, another embodiment for calculating the maximum signal strengthvalue will be described with reference to FIG. 17.

FIG. 17A to 17C are a graph showing a signal distribution of particledata which presents a plateau shape at the peak; a diagram showing theshape of the saturated signal portion; and an explanatory diagram forexplaining how the maximum signal strength value is calculated. FIG. 17Ashows the relationship between a signal waveform 1701 and a peak region1702, wherein the peak region 1702 in the signal waveform 1701 does notinclude data exceeding the saturated level since the peak region 1702reaches the saturation region of the light detector unit 104. FIG. 17Bshows a cross-section of the signal waveform 1701, where the verticalaxis represents the signal strength, and the horizontal axis representsthe pixel position in the signal. In FIG. 17B, a saturation level 1703indicates the saturation level of the light detector unit 104, and asignal width 1704 indicates the width of the peak region 1702. Also, asignal strength 1705 is a maximum signal strength value which isgenerated when an unsaturable detector is used for the light detectorunit 104.

Next explained is a method of calculating the maximum signal strengthvalue 1705 from the saturated signal waveform 1701. Assuming that thesaturation level 1703 is represented by SL; the signal width 1704 by SW,and the signal strength 1705 by PL, the illustrated waveform isapproximated to a Gaussian distribution to derive the followingequations:SL=k/σ·exp(−(−SW/2)²/(2·σ²))PL=k/σwhere k is a coefficient, and σ is a value calculated from theconfiguration of the optical system in the apparatus for inspectingparticles and defects of the present invention.

Therefore, from the two equations, PL is calculated as follows:PL=SL/exp(−(−SW/2)²/(2·σ²))Here, since SL indicates the output of the light detector unit 104 whenit is saturated, SL represents 255 gradation levels when an A/Dconverter of the light detector unit 104 has a 8-bit resolution. σ isgiven a value from zero to one depending on the configuration of theoptical system. Next, a method of calculating SW will be described. FIG.17C shows the shape of the peak region 1702, in other words, a region inwhich the light detector unit 104 is saturated. FIG. 17C includes asaturation region 1706 and a signal width 1704. Since the signalwaveform 1701 is regarded as a Gaussian distribution, the saturationregion 1706 can be assumed to be circular. Therefore, assuming that thesignal width 1704 is represented by SW, and the saturation region 1706by SA, SW is calculated by:SW=2·√{square root over ((SA/π))}In the above equation, √(A) represents a calculation of a square root ofA, and π is the Ludolphian number. The saturation region 1706 may becomprised of the number of pixels in which the light detector unit 104is saturated. Here, a saturated pixel may be represented by a maximum ofthe output from the A/D converter of the light detector unit 104, andmay be set in consideration of electric noise in the light detector unit104. For example, when the A/D converter has an 8-bit resolution, theoutput represents a maximum of 255 gradation levels. It may be thoughtthat the output at 245th gradational level or higher is saturated ifelectric noise accounts for 10 gradation levels.

If the signal waveform 1701 is not saturated, a similar calculation maybe performed using a maximum of the signal waveform 1701 as thesaturation level 1703.

Since the maximum signal strength value can be calculated from theforegoing process, the size of a detected particle can be measured bycomparing the values calculated using the standard particles with avalue calculated using the detected particle.

While the foregoing description has been made for the maximum signalstrength value as an example, the integral of signal strength overparticle data may be used instead of the maximum signal strength value.In this case, the integral of signal strength over particle data may becalculated by adding contrast values of respective pixels in thedetected particle signal. Also, while the foregoing embodiment employsan 8-bit A/D converter, an A/D converter having 10 bits or more may beused. Further, while the foregoing embodiment has been described for anexample of calculating the signal width 1704 as the diameter of acircle, a width of the saturation region which indicates a maximumlength or a minimum length may be used instead of the diameter.

In the description on the configuration of the apparatus, theillumination optical system 101 uses laser light as an example in theforegoing embodiment. Alternatively, white light may be used instead oflaser light. Also, when an object under testing has repeated circuitpatterns, the foregoing measurement of the size may be made after takinga difference between an image of the repeated pattern on which noparticle exists and an image of the same on which a particle exists.Also, irrespective of the presence or absence of repeated patterns, ifdata on scattered light or data on reflectivity associated with thecircuit pattern or a film, for example, an oxide film or a metal film,can be acquired beforehand, such data may be used to correct data on thesize of a particle on the circuit pattern or the film. Furthermore,while the foregoing embodiment measures the size of a particle bycomparing it with the sizes of standard particles, the size of theparticle may be compared with a particle, the size of which is known,instead of the standard particles.

Next, an exemplary method of calculating a particle size from themaximum signal strength value will be described with reference to FIG.15 when using data on a particle, the size of which is known. FIG. 15 isa graph in which the horizontal axis represents a maximum signalstrength value of particle acquired from the apparatus for inspectingparticles or defects according to the present invention, and thevertical axis represents the particle size. Here, the maximum signalstrength values of particles are calculated by the aforementionedmethod, while the size of a particle is derived by measuring ahorizontal dimension and a vertical dimension of the particle using areview apparatus such as a measuring SEM, multiplying the horizontaldimension by the vertical dimension, and taking a square root of theproduct. In FIG. 15, a plot point 1501 indicates data on a particle, sothat FIG. 15 indicates data on a plurality of particles. An approximatecurve 1502 is calculated by a least-square method based on the data atthe plot points 1501. In this event, the approximate curve can beexpressed by an equation y=a·x+b when the horizontal axis of the graphis represented by x, and the vertical axis of the same by y, where, aand b are values found by a least-square method.

For calculating a particle size from a maximum signal strength value, arelational expression between the maximum signal strength value and theparticle size is found and is used to calculate the particle size fromthe maximum signal strength value.

Next, the operation will be described. First, the approximate curve 1502has been previously calculated by the aforementioned method. Next, anobject under inspection is inspected using the apparatus for inspectingparticles or defects according to the present invention. Then, a maximumsignal strength value for the particle is calculated as described aboveduring the inspection. In this event, using the approximate curve, themaximum signal strength value is substituted into x of the approximatecurve to calculate y which is determined as the particle size.

Examples of the results calculated by the foregoing method are shown inFIGS. 30A, 30B and 31. FIGS. 30A, 30B are graphs, wherein the horizontalaxis represents the particle size calculated from signal outputted fromthe apparatus for inspecting particles or defects according to thepresent invention, and the vertical axis represents the particle sizemeasured by a measuring SEM. A plot point 3101 corresponds toinformation on one particle. A straight line 3102 in turn represents anapproximate line when each of plot points 3101 is least-mean-squareapproximated, and a value 3103 indicates a correlation value at the plotpoint 3101.

Further, FIG. 30A shows the result of measuring sizes of particlesdetected on a wafer having a one-layer pattern, and FIG. 30B shows, byway of example, the result of measuring sizes of particles detected on awafer having a multi-layer pattern.

FIG. 31 shows, by way of example, SEM photographs of used particles inaddition to the particle sizes calculated from signals outputted fromthe apparatus for inspecting particles or defects according to thepresent invention on the horizontal axis, and the particle sizesmeasured by the measuring SEM on the vertical axis, in a manner similarto FIGS. 30A, 30B.

While this embodiment calculates a square root of the vertical dimensionand the horizontal dimension of each particle, the size of a particlemay be defined as the larger one of the vertical dimension and thehorizontal dimension of the particle, or an average value of thevertical dimension and the horizontal dimension of the particle.Alternatively, the major axis of a particle may be used, or the minoraxis of the particle may be used. Further, the approximate curve may bea first-order curve, i.e., a straight line, or a higher-order curve, alogarithmic curve or an exponential curve, or a combination of aplurality of curves.

If the provision of different approximate curves for respective shapesof particles results in a better correlation of the particle sizescalculated as described above to the particle sizes measured using themeasuring SEM, a different approximate curve may be used for each shapeof particle. Here, the difference in the shape of a particle refers to,for example, the difference between a spherical particle and a flatplate-shaped particle, or the difference between a particle and ascratch, when the difference lies in the ratio of the particle sizemeasured from above to the particle size measured from the side.

Now, a method of distinguishing a particle from a scratch will bedescribed with reference to FIGS. 18A, 18B. FIG. 18A illustrates theconfiguration for discriminating between a particle and a scratch, andFIG. 18B shows how they are discriminated. FIG. 18A comprises asubstrate 1801; a particle 1802; epi-illumination light 1803 whichilluminates the substrate from a perpendicular direction; obliqueillumination light 1804; a light detector 1805; a storage circuit 1806;and a comparator circuit 1807. In the illustrated configuration, theepi-illumination light 1803 is emitted to the substrate at an angleclose to a direction perpendicular to the surface of the substrate 1801,while the oblique illumination light 1804 is emitted to the substrate1801 at an angle close to a direction horizontal to the substrate 1801.Their light sources may be an Ar laser, a YAG laser, or the like, by wayof example. The light detector 1805, in turn, may be a TV camera, a CCDlinear sensor, a TDI sensor, or a photomultiplier.

Next, the operation will be described. A particle or a scratch isirradiated with the epi-illumination light 1803 to detect scatteredlight from the particle or scratch by the light detector 1805. Theamount of scattered light is stored in the storage circuit 1806.Subsequently, the irradiation of the epi-illumination light 1803 isstopped, and the oblique illumination light 1804 is irradiated to theparticle or scratch to detect scattered light from the particle orscratch by the light detector 1805. The amount of scattered light isstored in the storage circuit 1806. Next, the light intensities, or theamounts of scattered light stored in the storage circuit 1806 arecompared by the comparator circuit 1807. The comparator circuit 1807calculates the ratio of the amount of scattered light when theepi-illumination light 1803 is irradiated to the amount of scatteredlight when the oblique illumination light 1804 is irradiated, andcompares the ratio with a previously determined threshold to determine aparticle or a scratch. A determination method used herein may takeadvantage of the fact that a particle has a smaller ratio of the amountsof scattered light, and a scratch has a larger ratio, as shown in FIG.18B.

Next, a method of calculating a particle size when there are a pluralityof approximate curves will be described with reference to FIG. 19. FIG.19 comprises a storage unit 1901 for storing a maximum of detectedsignals; a discrimination unit 1902 for discriminating between aparticle and a scratch; a conversion curve selection unit 1903; and aparticle size calculation unit 1904.

Next, the operation will be described. First, a conversion equation forcalculating a particle size from a maximum signal strength value usingthe aforementioned method has been created for each of a particle and ascratch in the apparatus of inspecting particles or defects according tothe present invention and stored in the conversion curve selection unit1903. Next, a wafer is inspected by the inspection apparatus. In thisevent, a maximum signal strength value of a detected substance is storedin the storage unit 1901. Next, the discrimination unit 1902 determineswhether the detected substance is a particle or a scratch by theaforementioned method. Based on this determination, a conversion curveis selected from the conversion curve selection unit 1903, and theselected conversion curve and the maximum signal strength value storedin the storage unit 1901 are inputted to the particle size calculationunit 1904 to calculate the size of the particle.

While the foregoing embodiment has described for an example in which aconversion curve is set according to the shape of a particle and adefect, a different approximate curve may be used according to theposition on an object under inspection at which a particle is detected,for example, whether a particle on a circuit pattern or a particle on aregion without patterns. Alternatively, a different approximate curvemay be used depending on the surface state of an object underinspection, for example, whether the surface is coated with an aluminumfilm or a tungsten film.

[Method of Calibrating Measured Particle Size]

Next described will be a method of calibrating a particle size measuredby the apparatus for inspecting particles or defects according to thepresent invention. This calibration may be used, for example, when theamount of illumination light has changed due to a deterioration in theillumination optical system in the apparatus for inspecting particles ordefects according to the present invention.

An exemplary calibrating method will be described. First, mirror waferswith standard particles having known sizes attached thereto is preparedas calibration wafers. Two or more types of standard particles arepreferably prepared. For example, a standard particle of 0.2 μm and astandard particle of 0.6 μm are attached to mirror wafers, respectively.Next, these wafers are inspected by the apparatus for inspectingparticles or defects according to the present invention to display thesizes of detected particles. In this event, if the inspection apparatusdoes not fail, peaks will appear at 0.2 μm and 0.6 μm on the scale ofthe histogram.

For example, FIG. 26 is a graph showing the number of detected particleson the vertical axis, and sizes of the detected particles on thehorizontal axis. As can be seen in FIG. 26, the number of detectedparticles is increased at 0.2 μm and 0.6 μm on the scale. In contrast toFIG. 26, FIG. 27 shows an example when the laser light source used inthe illumination optical system 101 has deteriorated to reduce theamount of illumination light to one half, wherein the number of detectedparticles is increased at 0.1 μm and 0.3 μm on the scale. In otherwords, FIG. 27 shows an example in which a reduced amount ofillumination light results in a less amount of scattered light, so thatparticle sizes are measured smaller than correct values.

Next explained will be a method of calculating a calibration coefficientfor calibrating the inspection apparatus. Assume first that the size ofthe standard particle inspected above is SS, and the size of a particlemeasured by the inspection apparatus of the present invention is IS. Inthis event, since a reduced amount of illumination light is calculatedfrom the ratio of SS to IS, the calibration coefficient, designated VR,is calculated by:VR=SS/ISTherefore, the calibration may be accomplished by increasing the amountof illumination light by a factor of VR or by multiplying a conversionequation for calculating the a particle size from the amount ofscattered light by VR. Specifically, in the aforementioned example,assuming that the size SS of the standard particle is 0.2 μm and thesize IS of the particle measured by the inspection apparatus is 0.1 μm,the calibration coefficient VR is calculated as:VR=2so that the amount of illumination light may be increased twice.

While the foregoing example has employed a wafer with a standardparticle of a known size attached thereto as a calibration wafer, thecalibration wafer is only required to have a particle or a defect ofknown size attached thereto, so that a wafer having a defect of knownsize intentionally created therein may be used instead.

Next, another calibration method will be described with reference toFIG. 2.

This is a method which uses values measured by the review apparatus asparticle sizes. First, an inspection is made in the particle inspectionapparatus 1301, and information on selected particles is added to theresults of inspection by the particle inspection apparatus 1301, forexample, serial numbers allocated to particles when they were detected,information on the positions of the particles, information on the sizesof the particles, and so on, and transmitted to the data server 1302through the network 1306. After the wafer has been conveyed to thereview apparatus 1303, the wafer is reviewed by the review apparatus1303, and information on particle sizes measured therein is added to theinspection result. Here, the particle size information is derived, whenusing, for example, a measuring SEM as-the review apparatus 1303, bymeasuring the horizontal dimension and vertical dimension of a particleusing the measuring SEM, multiplying the horizontal dimension by thevertical dimension, and taking a square root of the product. Next, theinformation added to the inspection result is transmitted to the dataserver 1302, and the added information is received by the particleinspection apparatus 1301 to calibrate the particle size informationoutputted from the particle inspection apparatus 1301 based on the sizeinformation.

The calibration method will be described with reference to FIG. 28. FIG.28 is a graph showing the information on the size of each particlemeasured by the particle inspection apparatus 1301 on the horizontalaxis, and the information on the size measured by the review apparatus1303 on the vertical axis. In FIG. 28, a plot point 2901 indicatesinformation on the size of the same particle, so that FIG. 28 plotsinformation on a plurality of particles. Here, if the particle sizes arecorrectly measured, plot points 2901 should be arranged along a straightline 2902. The calibration method first finds an approximate line forthe data of the plot points 2901 through a least-square method or thelike. This approximate line is the straight line 2903 which is expressedby an equation:y=a·x+bwhere x represents the size of a particle measured by the inspectionapparatus on the horizontal axis, and y represents the size of theparticle measured by the review apparatus 1303 on the vertical axis.Also, a and b are values found by a least-square method. Next, theparticle is inspected by the apparatus for inspecting particles ordefects according to the present invention, the size of the particle ismeasured, and the measured size is substituted into x in the aboveequation. The resulting value y is determined as the size of theparticle after calibration.

While the linear approximation has been described as the calibrationmethod, the approximation may be made to a higher order curve, alogarithmic curve, an exponential curve, or a combination of curves. Inaddition, a wafer for use in calibrating the particle size is notlimited to one, but a plurality of wafers may be used.

In the foregoing description, particles are inspected using scatteredlight. This method is advantageous in that particles can be efficientlyfound. Also advantageously, when particle sizes are calculated by theaforementioned method, particles can be found without requiring aspecial light source for measuring the sizes, and measurements of thesizes can be made with scattered light from the same light source.

[Analysis on Cause of Failure and Display of Result]

Next, description will be made on a procedure for analyzing a cause offailure and a procedure for displaying the result of analysis to theuser when particle sizes are measured using the apparatus for inspectingparticles or defects according to the present invention.

FIGS. 5A to 5C are diagrams showing that the relationship betweenparticle sizes and the number of detected particles changes due to acause of failure.

FIG. 6 is a line graph showing the number of detected particles andparticle sizes.

FIG. 7 is a histogram showing the number of detected particles andparticle sizes.

FIGS. 8A, 8B are schematic diagrams each clearly showing particles of aparticular size on a wafer;

FIGS. 9A to 9C are graphs each showing a transition of the number ofdetected particles for each particular size.

FIG. 10 is a diagram illustrating a screen for displaying to the user acause by which particles are generated.

FIG. 20 is a histogram showing the number of detected particles and theparticle sizes on a plurality of wafers.

FIG. 21 is another histogram separately showing detected particles andscratches on a wafer.

One important idea of the present invention is to use particle sizeinformation for analyzing a cause of failure. The following descriptionwill be made on the effectiveness of using the particle size informationfor analyzing a cause of failure.

Assume herein that particles have been detected from a wafer processedby a semiconductor manufacturing apparatus, for example, an etchingapparatus, and the relationship between particle sizes and the number ofdetected particles are as shown in FIGS. 5A to 5C. A region 401 in FIG.5A shows a distribution of particles steadily generated in a process ofan etching apparatus. In this case, the particle sizes concentrate in arange from a to b, so that a gently-sloping mountain is formed.

On the other hand, FIG. 5B shows an exemplary distribution of particleswhich are generated when the apparatus is faulty. In this case, largeparticles (a range of sizes larger than c) are frequently generated asshown in a region 402, in addition to the particles in the steady stateshown in the region 401. It is contemplated that the cause for suchlarge particles is deposits on the inner wall surface of the etchingapparatus are peeled off the wall surface during the etching process.FIG. 5C also shows an exemplary distribution of particles which aregenerated when a failure occurs. In this case, FIG. 5C shows thatparticle sizes also concentrate in a range from d to e in addition tothe particles in the steady state. It is contemplated that the cause forsuch particles is particular patterns which are peeled off and dispersedduring the etching process.

As described above, in manufacturing apparatuses for semiconductor orthe like, there is a relationship between the sizes of generatedparticles and the cause by which the particles are generated, so thatthe cause for particles generated in a certain manufacturing apparatuscan be immediately known by managing the generation of particles ofparticular sizes. In other words, by investigating the relationshipbetween the size of particles and the number of generated particles, thecause of failure can be revealed.

It should be understood that the values a–e of course depend onparticular manufacturing apparatuses, manufacturing processes and so on.Also, particles generated by a different cause may exhibit a differentdistribution of size, so that it is preferred to prepare data whichconforms to a particle size distribution for each cause. In addition,while this embodiment intends to identify the cause for generatedparticles in two ranges, the range of particle size may be divided intomore than two ranges.

Next, description will be made on a specific function of analyzing acause of failure.

First described is how the particle sizes and the number of detectedparticles are displayed on the data display unit 106. The data displayunit 106 displays a graph showing a particle size distribution asdescribed above, i.e., a graph which allows the user to understand therelationship between particle sizes and the number of detectedparticles. FIG. 6 is a graph showing the particle size on the horizontalaxis and the number of detected particles on the vertical axis. A point501 indicates the number of detected particles of certain size. In thisexemplary graph, data on the number of detected particles is provided inincrements of 0.1 μm. A curve 502 is a line connecting the points 501.By displaying the graph as in this embodiment, it can be immediatelyseen how particles detected from an object under inspection 102 aredistributed.

In the graph of FIG. 6, a minimum value on the horizontal axis may be aminimal detectable dimension of the particle inspection apparatus, or aparticle size which should be managed on a semiconductor manufacturingline. Also, the scale may be represented in a logarithmic or linearform. The unit of scale may be variable. Further, a displayed range ofeach axis may be fixed or variable. For example, particles generated bya particular cause alone may be displayed by displaying particles of aparticular size. The contents represented on the vertical axis and thehorizontal axis may be replaced with each other. Instead of the numberof detected particles, the density of particles may be shown. Further,while this embodiment displays a graph, an average value of the graph,and a standard deviation or variance of the graph may also be displayedother than the graph.

Also, while this embodiment displays particle data on one wafer as onegraph, the graph need not be displayed for only one wafer. An averagevalue, a standard deviation and a variance of particle data on aplurality of wafers may be displayed, and particle data on a pluralityof wafers may be displayed side by side.

The graph may be displayed in histogram as shown in FIGS. 7 and 32. Thegraphs on these figures indicate the particle size on the horizontalaxis, and the number of detected particles on the vertical axis,similarly to FIG. 6. These graphs display the particle size on thehorizontal line divided into certain sections. FIG. 7 shows datasections in increments of 0.2 μm. FIG. 32 in turn shows data sections inincrements of 0.1 μm, wherein particles having the size equal to or morethan 5 μm are counted in a bar graph 3301, and a histogram for particleshaving the size smaller than 1.1 μm and a histogram for particles havingthe size equal to or larger than 1.1 μm are displayed in differentcolors, by way of example. In addition, a function may be added fordisplaying information on the positions of a detected particles in aselected portion of a bar graph. Also, a review image may be displayedfor the detected particles in the selected portion.

FIG. 34 shows another example of graphical representation. FIG. 34 showsan example in which the particle size is set on the horizontal axis, andan accumulated number of particles is set on the vertical axis. Here,the accumulated number refers to the number of detected particles of acertain size or larger.

FIG. 35 shows a further example of graphical representation. FIG. 35shows an example in which the particle size is set on the horizontalaxis, and the number of detected particles is set on the vertical axis,with a curve 3601 indicative of the number of detected particles, and anequation expressing the curve 3601 indicative of the number of detectedparticles additionally indicated in the graph. In the equation 3601, xrepresents the particle size, and y the number of detected particles.The equation 3601 is an approximate equation derived from the number ofdetected particles for each particle size. The curve 3601 represents theequation 3602.

FIG. 20 shows a further example of graphical representation. While theexample in FIG. 7 displays data for one wafer, data on a plurality ofwafers may be displayed side by side as shown in FIG. 20. Specifically,FIG. 20 is an example in which the number of detected particle is set onone of three coordinate axes; the particle size on another axis; and thewafer number on the remaining axis. In this example, data sections forthe particle size are set in increments of 0.1 μm from zero to 1 μm,particles having sizes equal to or larger than 1 μm are counted on thesame bar graph, and the total number of detected particles is alsodisplayed in the graph. As is the case with FIG. 6, an average value,standard deviation and variance may also be displayed on the graph ofFIG. 20.

FIG. 21 shows a further example of graphic representation. FIG. 21 showsan example in which displayed data are classified into particles andscratches and also classified by size.

Next, description will be made on a function of displaying informationon the positions of detected particles. FIG. 8A shows information on thepositions of all particles detected by a particle inspection.

In FIG. 8A, detected particles 702 exist within a contour 701 of an8-inch semiconductor wafer. In this event, as a mouse is click once ortwice on a bar graph 601 in FIG. 7, the section of the bar graph 601,i.e., displayed particles 703 of sizes ranging from 2.8 μm to 3.0 μm inFIG. 8A are changed as shown in FIG. 8B. The inspection apparatus hassuch a function so that the user can immediately find the positions onan object under inspection 102 of particles having sizes in a particularrange.

FIG. 22 shows an exemplary result of a particle inspection displayedafter the inspection. The display in FIG. 22 comprises an inspection map2201 indicative of the positions at which particles are detected; ahistogram 2202 for the sizes of the detected particles; a review button203; a review image 2204 of the detected particles; particles 2205; aparticle size data section 2206 to be reviewed. The review image 2204 isdisplayed centered at the particle 2205. In this example, particleshaving sizes ranging from 2.8 μm to 3.0 μm in the data section 2206 areselected.

In operation, after particles are inspected by the apparatus forinspecting particles or defects according to the present invention, theinspection map 2201 is displayed as information on the positions of theparticles, and the histogram 2202 is displayed as information onparticle sizes. Then, the data section 2206 is selected as a particlesize to be reviewed. Clicking on the review button 2203 causes thereview image 2204, provided by the apparatus for inspecting particles ordefects of the present invention, to be displayed. Here, the reviewimage 2204 may be an image generated from scattered laser light, or animage captured by a microscope.

Next, a management approach applied when the statistics are collected intime series on particles having a particular size will be described withreference to FIGS. 9A to 9C.

FIG. 9A shows a transition of the total sum of all particles,irrespective of the size, detected by the particle inspection apparatus,in time series for wafers processed in the same process by the samemanufacturing apparatus. FIG. 9C shows a transition of the total sum ofparticles having sizes ranging from 2.8 to 3.0 [μm], shown in theexample of FIG. 7, in time series. FIG. 9B shows a transition of thetotal sum of the remaining particles in time series.

Thresholds 1001, 1002, 1003 indicate management reference values for thenumber of particles in the three cases. When particles exceeding thesethresholds are detected, this means that an associated wafer isdiagnosed as defective. Specifically, it is determined from FIG. 9A thata peak value 1004 near an inspection time A is unusually high.

However, while a certain failure may be guessed from the statisticsshown in FIG. 9A, its cause cannot be revealed.

On the other hand, when particles are managed by size in accordance withthe inspection approach of the present invention, a remarkable peak 1005appears at A time in FIG. 9C, so that it is understood that particleshaving sizes ranging from 2.8 to 3.0 [μm] particularly concentrate in alot which was inspected at that time. Thus, from the fact that nosection exceeds the threshold in FIG. 9B and the peak value 1005 issensed in FIG. 9C, the user can guess by the reason shown in FIGS. 5A to5C that patterns of these sizes peeled off and scattered on wafersduring an etching process can be the cause for an unusual increase inthe number of particles, and therefore immediately take effectivecountermeasures to the failure, such as checking the etching apparatus.

Next, an example of displaying a cause of failure to the user will bedescribed with reference to FIG. 11.

The apparatus for inspecting particles or defects according to thepresent invention has a function of analyzing the particle size and thenumber of detected particles to display a cause of failure to the user.

For example, assume that a graph as shown in FIG. 7 results from aninspection, taking the cause of failure shown in FIG. 5C as a model.Assume also that a section d–e in FIG. 5C corresponds to the particlesize range of 2.8 μm to 3.0 μm in FIG. 7. Therefore, when the result ofinspection shown in FIG. 7 is obtained, the screen shown in FIG. 9 isdisplayed to clarify the user the result of analysis on the cause offailure.

Next described is another exemplary management approach based on theparticle size. Particles detected by the inspection apparatus may beclassified into those which cause a failure, and those which do notcause a failure. Specifically, if particles are smaller than wire widthsand spaces between wires in a wiring pattern created on a wafer, suchparticles cause no failure in many cases. Therefore, detected particleshaving a certain size or more may be managed as a possible cause offailure.

Next, description will be made on an exemplary method of calculating aparticle size to be managed. FIG. 23 shows the relationship between awiring pattern 2401 having a wire width W1, a wiring pattern 2402 havinga wire width W2 and a wiring pattern having a wire width W3 on a wafer,and a particle 2404. When this particle 2404 is conductive, the particle2404 attached, for example, at a position 2405 to connect the wiringpattern 2401 and wiring pattern 2402 would cause the wiring pattern 2401and wiring pattern 2402 to short-circuit through the particle 2404, withthe result that this chip becomes defective. As such, assuming that thedistance between the wiring pattern 2401 and wiring pattern 2402 is S1,and the distance between the wiring pattern 2402 and wiring pattern 2403is S2, the particle 2404 which can short-circuit the wiring pattern 2402to another wire has a size of S1 or S2 or more. Particularly, a particlehaving a size of (S1+W2+S2) will short-circuit wires with possibility of100%.

Therefore, when the wiring patterns have the widths and distance betweenwires as defined above, the size of a particle causing a failure isgiven by: MIN (S1, S2) where MIN (A, B) indicates the smaller value of Aand B when they are compared.

It should be noted that the example shown herein is a calculation forthe most strict condition in management. If the condition is lessstrict, larger particles may be managed.

By determining a particle size to be managed in each manufacturingprocess by the calculation described above and monitoring fluctuationsin the number of detected particles having the managed size or more, itis possible to sense the occurrence of a failure without delay. Amonitoring method used herein may involve previously calculating anaverage and standard deviation of the number of particles undermanagement detected, for example, from several to several tens ofwafers, monitoring the number of particles based on a monitoringthreshold calculated by:Monitoring Threshold=Average+k·StandardDeviation and analyzing a cause of failure and taking countermeasures towafers on which the number of detected particles exceeds the monitoringthreshold. In the above equation, k is a constant which may be set tok=3, for example, when it is desired that the failure analysis isconducted for approximately 0.3% of all wafers.

Next described is another method of calculating a particle size to bemanaged. This method calculates the influence of particles exerted onthe yield of wafers from the presence or absence of particles detectedon one wafer, and determination made to chips on which the particles aredetected as to whether they are non-defective or defective, and managesa particle size at which the calculated influence present a maximum.

A method of calculating the influence on the yield will be describedwith reference to FIG. 29. FIG. 29 shows chips on a wafer classifiedaccording to the presence or absence of particles, and non-defective anddefective chips. Specifically, FIG. 29 shows chips 3001 (hereinafterlabeled “Gn”) on which no particles have been detected and which arenon-defective; chips 3002 (hereinafter labeled “Bn”) on which noparticles have been detected but which are defective; chips 3003(hereinafter labeled “Gp”) on which particles have been detected butwhich are non-defective; and chips 3004 (hereinafter labeled “Bp”) onwhich particles have been detected and which are defective. Here,whether or not particles have been detected on a certain chip may bedetermined based on the position information in the result of aninspection performed by the apparatus for inspecting particles ordefects according to the present invention. Also, determination as towhether a certain chip is non-defective or defective may be made using,for example, the result of an electric inspection.

First, assuming that the yield of a certain wafer is Y, and the yield ofchips on which no particles have been detected is Yn, the influence dYof detected particles on the yield of the wafer is defined as:dY=Yn−YSince Y is the yield of the wafer, Y can be expressed by:Y=Yn·(1−γ)+Yp·γwhere Yp is the yield of chips on which particles have been detected,and γ is the proportion of chips on which particles have been detectedwith respect to the total number of chips (hereinafter called the“particle occurrence frequency”).

Here, using the aforementioned Gn, Bn, Gp, Bp:Y=(Gn+Gp)/(Gn+Bn+Gp+Bp)Yn=Gn/(Gn+Bn)Yp=Gp/(Gp+Bp)γ=(Gp+Bp)/(Gn+Bn+Gp+Bp)can be derived.

Therefore, dY can be expressed as follows: $\begin{matrix}{{dY} = {{Yn} - Y}} \\{= {{Yn} - \left( {{{Yn} \cdot \left( {1 - \gamma} \right)} + {{Yp} \cdot \gamma}} \right)}} \\{= {\left( {{Yn} - {Yp}} \right) \cdot \gamma}} \\{= {{Yn} \cdot \left( {1 - {{Yp}/{Yn}}} \right) \cdot \gamma}}\end{matrix}$Here, assuming that the probability of a chip determined as defectivedue to particles is represented by F (hereinafter called the “criticalprobability”), Yp can be expressed by:Yp=Yn·(1−F)

Rewriting the above equation for F,F=1−Yp/Ynso that dY can be expressed by:dY=Yn·F·γ

Here, the particle occurrence frequency γ is larger as a particledetection sensitivity is higher, and smaller as the particle detectionsensitivity is lower. This is because a higher detection sensitivitycontributes to detection of a larger number of particles. The criticalprobability F in turn is smaller as the particle detection sensitivityis higher, and larger as the particle detection sensitivity is lower.This is because although a higher sensitivity contributes to detectionof smaller particles, those particles which are smaller than thedistance between wiring patterns do not cause a failure such asshort-circuiting.

Therefore, when the influence dY on the yield is calculated, theparticle sizes used in the calculation are limited. The particle sizewhich maximizes the influence dY on the yield indicates the minimumparticle size to be managed. The limitation on the particle sizes refersto using those data on particles having a certain size or more.

FIG. 24 shows an exemplary result of calculating the influence dY on theyield. FIG. 24 shows the influence dY on the yield on the vertical axis,and the particle size used in calculating the influence dY on the yieldon the horizontal axis. For example, in FIG. 24, a point 2501 indicatesthat the influence dY on the yield is 0.1 as a result of the calculationusing data on particles having sizes equal to or more than 0.1 μm, and apoint 2502 indicates that the influence dY on the yield is 0.8 as aresult of the calculation using data on particles having sizes equal toor more than 0.4 μm. Here, using data on particles having the sizesequal to or more than 0.1 μm means that the calculation is performed onthe assumption that among detected particles, chips on which particlesof 0.1 μm or more have been detected are regarded as chips on whichparticles are attached, and chips on which particles less than 0.1 μmhave been detected or no particles have been detected are regarded aschips on which no particles are attached. Thus, it is appreciated fromFIG. 24 that the influence dY on the yield is the largest when it iscalculated using data on particles of 0.4 μm or more, so that particlesof 0.4 μm or more should be managed.

While the foregoing embodiment shows that the particle size is changedin increments of 0.1 μm, the increment may be 0.2 μm or any other value.Also, while the foregoing embodiment has been described for an examplewhich determines the particle size that exerts the largest influence dYon the yield as the method of determining a particle size to be managed,the particle size to be managed need not be the particle size thatexerts the largest influence, but may be a particle size that presents avalue close to the largest influence dY on the yield, for example, avalue equal to or more than the largest influence dY multiplied by 0.9.

FIGS. 33A to 33C show another exemplary result of calculation. FIGS. 33Ato 33C show the result of calculating the influence dY on the yield; andparticle detection maps at that time. FIG. 33A shows, by way of example,that the influence dY on the yield is calculated in increments ofapproximately 0.07 μm of particle size, and values on the vertical axisare represented in percent. FIG. 33B is a particle detection map whichdisplays all particles detected by the apparatus for inspectingparticles or defects according to the present invention, and FIG. 33C isa particle detection map which shows extracted particles having thesizes equal to or more than 1.1 μm. The value of 1.1 μm indicates theparticle size that exerts the largest influence dY on the yield in FIG.33A. It is therefore understood that particles may be managed based onthe particle detection map of FIG. 33C.

Next, description will be made on an approach for managing asemiconductor device manufacturing process when the influence dY on theyield is used for the management. FIG. 25 shows a graph which sets theaforementioned influence dY on the yield on the vertical axis, and asemiconductor manufacturing process on the horizontal axis.Specifically, the horizontal axis shows steps in the process in whichparticles are inspected using the apparatus for inspecting particles ordefects according to the present invention.

Next, the operation will be described. First, an inspection is conductedin each of the steps in the process shown on the horizontal axis usingthe same wafer. Next, at the time each of chips on the wafer isdetermined as non-defective or defective, the aforementioned influencedY on the yield is calculated for each step. FIG. 25 is an example ofcalculating the influence dY on the yield in each step. For example, apoint 2601 indicates that the influence dY on the yield is 0.8 whencalculated using particles detected in a step labeled “Step 4” in theprocess. In this way, the influence dY on the yield is calculated ineach step, and countermeasures are taken preferentially from a stepwhich presents a larger influence dY on the yield, thereby making itpossible to take countermeasures from a step which is more likely tocause a failure.

In the foregoing embodiment, all data on particles detected in each stepare used for calculating the influence dY. For particles which have beenknown that they had occurred in a different step, the influence dY onthe yield may be calculated using the remaining data except for the dataon the particles. For removing data, for example, information on theposition of particles detected in Step 1 in FIG. 25 may be compared withinformation on the position of particles detected in Step 2, and theparticles previously detected in Step 1 may be deleted from data onparticles in Step 2.

Also, the foregoing embodiment has been described for the management ofparticle size using the influence dY on the yield expressed by:dY=Yn·F·γWhen a failure caused by a process is eliminated by improving theprocess management,dY=F·γmay be used by setting the aforementioned Yn to one (Yn=1). The approachof the present invention may also be applied to any index forcalculating the influence of particles. For example, for memory productssuch as DRAM, the number of defective bits caused by each particle maybe used as an index.

The foregoing embodiment is advantageous in that since wiring patternwidths and space widths in a semiconductor device are only required asinformation for determining whether a particle causes a failure in theexample described with reference to FIG. 23, a particle size to bemanaged can be determined at the time the design of a semiconductordevice is definite. The example described with reference to FIG. 29, inturn, is advantageous in that it employs an index including aconsideration of information such as short-circuiting of wires due tothe height of a particle, and so on, as well as the width of theparticle, so that the actual state of device can be known.

[Inspection on Particles by Region and Analysis on Cause of Failure]

Next, description will be made on an embodiment which manages particledata by region on a wafer to take countermeasures using the apparatusfor inspecting particles or defects according to the present invention.

FIG. 11 schematically illustrates regions on a semiconductor wafer.

FIGS. 12A, 12B are schematic diagrams each clearly showing particles ofa particular size on a wafer when particle data is managed separatelyfor each region;

FIGS. 13, 14 are graphs each showing the number of detected particles bysize in each region.

Generally, when a chip pattern is formed on a semiconductor wafer, thepattern is not always formed uniformly, but some region in the patternexhibits a higher pattern forming density while another region in thepattern exhibits a lower pattern forming density. For example, assumingthat a chip illustrated in FIG. 11 is a microprocessor, the pattern isdivided, for example, into a region 1101 for memory cell circuits; aregion 1102 for data input/output circuits; and a region 1103 in whichno circuit pattern exists. Generally, these regions 1101, 1102, 1103differ in circuit pattern integration degree from one another. As aresult, different sizes of particles would cause failures in therespective regions. In other words, the particle size which should bemanaged and analyzed differs from one region to another in a chip.

Specifically stated, for example, when a particle of size α or morewould cause the chip to be defective in the region 1101; a particle ofsize β or more in the region 1102; and a particle of size γ or more inthe region 1103, information on these regions and information onparticle size which causes the chip to be defective in each of theseregions are previously stored in the inspection apparatus as managementdata. The information on the regions and information on particle sizecausing the defective chip may be directly entered on a screen which maybe provided on the inspection apparatus for entering coordinate valuesand particle size, or regions may be selected from an optical imagecaptured by a TV camera or the like. Alternatively, data may bedownloaded from a higher rank system, or data may be read into theinspection apparatus from a removable storage medium, for example, afloppy disk.

By providing the inspection apparatus with the information on theregions and the information on particle sizes which cause the chip to bedefective, an object under inspection is inspected. Then, a region isdetermined from information on the position of a detected particle inthe inspection apparatus, and the information on the detected particlesize is compared with the information on particle sizes which cause thechip to be defective, to determine whether or not the detected particlewill cause a failure.

As a result, particles determined as a cause of failure and particlesnot determined as a cause of failure are displayed in different forms,such that the particles determined as a cause of failure aredistinctively displayed to the user, thereby allowing the user to beimmediately aware of the particles which cause a failure.

The foregoing approach will be shown in a specific manner with referenceto FIGS. 12A, 12B.

A wafer shown in FIGS. 12A, 12B is displayed with the positions ofdetected particles 1202 indicated thereon. Since the result of detectionhas been displayed as shown in FIG. 12A in the prior art, an analysis onthe cause of failure involves selecting proper particles and analyzingthe selected particles. Therefore, the prior art suffers from a lowprobability that particles which should be essentially analyzed can beselected, and a long time required for the analysis on the cause offailure. On the contrary, by displaying in a different form thoseparticles which have been determined as the cause of failure using theforegoing determination, i.e., particles 1203 which should be analyzedas shown in FIG. 12B, it is possible to readily select the particles1203 which should be analyzed from detected particles, to increase theprobability that the particles which should be analyzed can be selected,and to rapidly analyze the cause of failure. In FIG. 11, for displayingdifferent regions in different manners, they are displayed in differentpatterns. Alternatively, these region may be displayed in differentcolors or sizes. Further alternatively, displayed particles may belimited to those which cause a failure. Also, while the foregoingembodiment divides a chip into several regions, the wafer surface may bedivided, for example, in accordance with the distance from the center ofthe wafer to the wafer edge, and different particle sizes may be managedin different regions. Furthermore, the layout of semiconductor chips maybe displayed on the wafer shape 1201.

Next, description will be made on an approach for inspecting the numberof particles detected in respective regions to take countermeasures to afailure with reference to FIGS. 13 and 14.

In this example, a wafer is divided into three regions, designatedRegion A, Region B, Region C, in each of which the number of particlesis detected. Then, the result is displayed to the user in the form ofgraph for each region.

For example, as shown in FIG. 13, the horizontal axis represents theparticle size, and the vertical axis represents the number of detectedparticles, wherein different colors are allocated to Region A, Region B,Region C, respectively, the particles are displayed by size in graphicalrepresentation, and the numbers of particles falling under the same sizecategory in the three regions are displayed side by side.

Alternatively, as shown in FIG. 14, the numbers of particles fallingunder the same size category may be displayed in stack.

Specifically, the three regions may be a memory cell region, a circuitregion other than memory circuit, and region without circuit pattern,for example, on a semiconductor wafer. By displaying these regions asshown in FIGS. 13 and 14, the management of particles by region isfacilitated. The information on the regions may be directly entered on ascreen which may be provided on the inspection apparatus for enteringcoordinate values and particle size, or regions may be selected from anoptical image captured by a TV camera or the like. Alternatively, datamay be downloaded from a higher rank system, or data may be read intothe inspection apparatus from a removable storage medium, for example, afloppy disk.

Next described will be an approach for counting the number of detectedparticles by size in each of regions to find out defective products.

As described above, the particle size determined as a cause of failurediffers from one region to another. In a certain region which does notinclude very fine circuits, even a relatively large particle would notbe regarded as a cause of failure. On the other hand, in another regionwhich includes fine circuits, even a relatively small particle couldcause a trouble. In this way, thresholds over which an alarm isgenerated are designated by α, β, γ for Region A, Region B, Region C,respectively. For example, in the example shown in FIGS. 13, 14, assume:

-   -   α=1.0 [μm]    -   β=1.6 [μm]    -   γ=2.0 [μm]

With these thresholds, the total sum of detected particles exceeding thethreshold set for each region is as follows:

-   -   Region A . . . 24    -   Region B . . . 3    -   Region C . . . 1

Even though a very large number of particles are apparently detected inRegion C, they do not significantly affect the quality of a product. Onthe other hand, particles detected in Region A, the number of which isnot so large as in Region C, is highly likely to affect the quality ofthe product, so that the product could be determined as defective due tothe particles attached on Region A with a high probability. In this way,a reasonable inspection can be conducted in accordance with thecharacteristic of each region by setting a threshold of particle sizefor each region, over which a particle detected therein is regarded as acause of failure, counting the total sum of detected particles exceedingthe threshold in each region, determining whether the object undertesting is non-defective or defective, and displaying the user to theresult of determination.

[About Optical System in Apparatus for Inspecting Particles or Defects]

In the foregoing description on the present invention, the opticalsystem in the apparatus for inspecting particles or defects employsscattered light to detect particles and measure the sizes of theparticles. The approach of the present invention, however, can beapplied to an optical system which relies on reflected light to detectparticles or defects and measure the sizes thereof. Generally, theoptical system relying on scattered light exhibits a high inspectionefficiency but a low measurement accuracy. On the contrary, the opticalsystem relying on reflected light exhibits a low inspection efficiency,but a high measurement accuracy. The approach of the present inventioncan be applied to either of the optical systems.

As appreciated from the foregoing, the present invention provides anapparatus and method for inspecting particles ore defects, which aresuitable for use in inspecting particles or defects in processes formanufacturing semiconductor wafers or thin film substrates andconducting a failure analysis based on the inspection result. Theinspection apparatus and method are capable of rapidly takingcountermeasures to a failure by conducting an inspection and a failureanalysis in accordance with the characteristics of particles andpatterns or the characteristics of regions on an object underinspection.

The invention may be embodied in other specific forms without departingfrom the spirit or essential characteristics thereof. The presentinvention is therefore to be considered in all respects as illustrativeand not restrictive, the scope of the invention being indicated by theappended claims rather than by the foregoing description and all changeswhich come within the meaning and range of equivalency of the claims aretherefore intended to be the embraced therein.

1. An apparatus for inspecting defects comprising: illuminating meansfor irradiating light to an object under inspection; light detectingmeans for detecting reflected light or scattered light from the objectunder inspection; processing means for processing a signal output fromthe light detecting means to detect defects; classifying means forclassifying said defects detected by said processing means intocategories; dimension calculating means for processing the signalaccording to the classified categories to calculate a size of eachdefect; data processing means for processing an inspection result; anddisplay means for displaying information on the inspection result,wherein the data processing means relates a defect size to a cause offailure to estimate a cause of failure from statistical processing onthe inspection result, and the display means display information on theestimated cause of failure, and wherein said classifying meansclassifies said defects detected by said processing means into saidcategories in accordance with shape of said defects, and said dimensioncalculating means includes a storage unit in which a plurality ofconversion curves used for calculating defect size of said defects havebeen stored in advance, each of curves representing relationship betweenintensity of light detected by said light detecting means and defectsize, and being configured in accordance with shape of defect.
 2. Aninspection apparatus according to claim 1, wherein the display meansdisplays a distribution of frequencies for defect sizes measured by thedimension measuring means.
 3. An inspection apparatus according to claim1, wherein the display means displays defects having a particular sizein a manner discriminative from the remaining particles or defects. 4.An inspection apparatus according to claim 1, wherein the dataprocessing means performs a failure analysis by generating managementinformation for each of regions on the object under inspection,comparing the management information with sizes of defects detected fromeach region to evaluate whether each of the regions on the object underinspection is non-defective or defective in quality.
 5. An inspectionapparatus according to claim 4, wherein the display means displaysdefects having a particular size in each of the regions in a mannerdiscriminative from the remaining defects based on an evaluation result.6. An inspection apparatus according to claim 1, wherein the displaymeans displays the distribution of frequencies for defect sizes measuredby the dimension measuring means for each of the regions on the objectunder inspection.
 7. An inspection apparatus according to claim 1,wherein the dimension measuring means uses an integral of a signal valuedetected by the light detecting means.
 8. An inspection apparatusaccording to claim 1, wherein the dimension measuring means uses amaximum of a signal value detected by the light detecting means.
 9. Aninspection apparatus according to claim 1, wherein the illuminatingmeans illuminates white light to the object under inspection.
 10. Amethod of inspecting defects comprising the steps of: irradiating anobject under inspection with light; detecting reflected light orscattered light from the object under inspection; processing a signalindicative of detected reflected light or scattered light to detectdefects; classifying said defects detected by said processing intocategories; calculating a size of each defect by processing a signal ofsaid detected defect in accordance with said classified categories;processing data including data representative of the signal andincluding a result of measuring the size of each defect; and displayingthe result of data processing, wherein the step of processing dataincludes estimating a cause of failure, and the step of display includesdisplaying information on an inspection result, and wherein the step ofclassifying includes classifying said defects into said categories inaccordance withy shape of said defects and the step of calculatingincludes storing a plurality of conversion curves used for calculatingdefect size of said defects in a storage unit in advance, each of curverepresenting relationship between intensity of light detected by saidlight detecting means and defect size, and being configured inaccordance with shape of defect.
 11. A method of inspecting defectsaccording to claim 10, wherein the step of displaying includesdisplaying a distribution of frequencies for particle or defect sizesmeasured by the step of measuring.
 12. A method of inspecting defectsaccording to claim 10, wherein the step of displaying includesdisplaying defects having a particular size in a manner discriminativefrom the remaining defects.
 13. An inspection apparatus according toclaim 1, wherein said classifying means classifies said defects intocategories including particle and scratch.
 14. An inspection apparatusaccording to claim 1, wherein said classifying means classifies saiddefects into categories including particles by shape.
 15. A method ofinspecting defects according to claim 13, wherein in said step ofclassifying, said categories including particle and scratch.
 16. Amethod of inspecting defects according to claim 13, wherein in said stepof classifying, said categories including particles by shape.